This paper proposes a novel algorithm in pixel-based pattern recognition in design layout which offers simplicity, speed and accuracy to recognize any patterns that later can be used to detect problematic pattern in lithography process so they can be removed or improved earlier in design stage.:Abstract 1 Content 3 List of Figure 6 List of Tables 8 List of Abbreviations 9 Chapter 1: Introduction 10 1.1 Motivation 10 1.2 Related Work 11 1.3 Purpose and Research Question 12 1.4 Approach and Methodology 12 1.5 Scope and Limitation 12 1.6 Target group 13 1.7 Outline 13 Chapter 2: Theoretical Background 14 2.1 Problematic Pattern in Computational Lithography 14 2.2 Optical Proximity Effect 16 2.3 Taxonomy of Pattern Recognition 17 2.3.1 Feature Generation 18 2.3.2 Classifier Model 19 2.3.3 System evaluation 20 2.4 Feature Selection Technique 20 2.4.1 Wrapper-Based Methods 21 2.4.2 Average-Based Methods 22 2.4.3 Binary Geometrical Transformation 24 2.4.3.1 Image Interpolation 24 2.4.3.2 Geometric Transformation 26 2.4.3.2.1 Forward Mapping: 26 2.4.3.2.2 Inverse Mapping: 27 2.4.3.3 Thresholding 27 2.5 Machine Learning Algorithm 28 2.5.1 Linear Classifier 29 2.5.2 Linear Discriminant Analysis (LDA) 30 2.5.3 Maximum likelihood 30 2.6 Scoring (Metrics to Measure Classifier Model Quality) 31 2.6.1 Accuracy 32 2.6.2 Sensitivity 32 2.6.3 Specifity 32 2.6.4 Precision 32 Chapter 3: Method 33 3.1 Problem Formulation 33 3.1.1 T2T Pattern 35 3.1.2 Iso-Dense Pattern 36 3.1.3 Hypothetical Hotspot Pattern 37 3.2 Classification System 38 3.2.1 Wrapper and Average-based 38 3.2.2 Binary Geometric Transformation Based 39 3.3 Window-Based Raster Scan 40 3.3.1 Scanning algorithm 40 3.4 Classifier Design 42 3.4.1 Training Phase 43 3.4.2 Discriminant Coefficient Function 44 3.4.3 SigmaDi 45 3.4.4 Maximum Posterior Probability 45 3.4.5 Classifier Model Block 46 3.5 Weka 3.8 47 3.6 Average-based Influence 49 3.7 BGT Based Model 50 Chapter 4: Results 55 4.1 Wrapper and Average-based LDA classifier 55 4.2 BGT Based LDA with SigmaDi Classifier 56 4.3 Estimation Output 57 4.4 Probability Function 58 Chapter 5: Conclusion 59 5.1 Conclusions 59 5.2 Future Research 60 Bibliography 61 Selbstständigkeitserklärung 63

As the semiconductor technology roadmap further extends, the development of next generation silicon systems becomes critically challenged. On the one hand, design and manufacturing closures become much more difficult due to the widening gap between the increasing integration density and the limited manufacturing capability. As a result, manufacturability issues become more and more critically challenged in the design of reliable silicon systems. On the other hand, the continuous scaling of feature size imposes critical issues on traditional interconnect materials (Cu/Low-K dielectrics) due to power, delay and bandwidth concerns. As a result, multiple classes of new materials are under research and development for future generation technologies. In this dissertation, we investigate several critical Computer-Aided Design (CAD) challenges under advanced nanolithography and nanophotonics technologies. In addressing these challenges, we propose systematic CAD methodologies and optimization techniques to assist the design of high-yield and high-performance integrated circuits (IC) with low power consumption. In Very Large Scale Integration (VLSI) CAD for nanolithography, we study the manufacturing variability under resolution enhancement techniques (RETs) and explore two important topics: (1) fast and high fidelity lithography hotspot detection; (2) generic and efficient manufacturability aware physical design. For the first topic, we propose a number of CAD optimization and integration techniques to achieve the following goals in detecting lithography hotspots: (a) high hotspot detection accuracy; (b) low false-positive rate (hotspot false-alarms); (c) good capability to trade-off between detection accuracy and false-alarms; (d) fast CPU run-time; and (e) excellent layout coverage and computation scalability as design gets more complex. For the second topic, we explore the routing stage by incorporating post-RET manufacturability models into the mathematical formulation of a detailed router to achieve: (a) significantly reduced lithography-unfriendly patterns; (b) small CPU run-time overhead; and (c) formulation generality and compatibility to all types of RETs and evoling manufacturing conditions. In VLSI CAD for nanophotonics, we focus on three topics: (1) characterization and evaluation of standard on-chip nanophotonics devices; (2) low power planar routing for on-chip opto-electrically interconnected systems; (3) power-efficient and thermal-reliable design of nanophotonics Wavelength Division Multiplexing for ultra-high bandwidth on-chip communication. With simulations and experiments, we demonstrate the critical role and effectiveness of Computer-Aided Design techniques as the semiconductor industry marches forward in the deeper sub-micron (45nm and below) domain. / text

With podcasts being a fast growing audio-only form of media, an effective way of promoting different podcast shows becomes more and more vital to all the stakeholders concerned, including the podcast creators, the podcast streaming platforms, and the podcast listeners. This thesis investigates the relatively little studied topic of automatic podcast trailer generation, with the purpose of en- hancing the overall visibility and publicity of different podcast contents and gen- erating more user engagement in podcast listening. This thesis takes a hotspot- based approach, by specifically defining the vague concept of “hotspot” and designing different appropriate methods for hotspot detection. Different meth- ods are analyzed and compared, and the best methods are selected. The selected methods are then used to construct an automatic podcast trailer generation sys- tem, which consists of four major components and one schema to coordinate the components. The system can take a random podcast episode audio as input and generate an around 1 minute long trailer for it. This thesis also proposes two human-based podcast trailer evaluation approaches, and the evaluation results show that the proposed system outperforms the baseline with a large margin and achieves promising results in terms of both aesthetics and functionality.